Examples of using Real-time processing in English and their translations into Chinese
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Stream processing: The real-time processing of data.
Software interface is simple, easy to secondary development and real-time processing.
Because conversation requires real-time processing, several seconds is really not practical.
Real-time processing and smart search have made finding answers in a sea of big data easier than ever before.
Hadoop is not efficient for real-time processing of data.
Now, real-time processing software has spread beyond Wall Street and the City to other industries.
Hadoop is not efficient for real-time processing of data.
This increase in real-time processing means you will be deploying tech capable of handling and managing 5G.
However, Hadoop was not designed for real-time processing of data.
The increase in real-time processing capabilities means that people will deploy technologies capable of processing and managing 5G.
Advances in computing and data science have made real-time processing and analysis of big data a reality.
Every major tech company has already figured out that the future is in data,most specifically, the real-time processing of it.
Modern applications are driving the need for low latency, real-time processing and the ability to process millions of requests per second.
The heavy hitter tech companies are figuring out that the future is in data-most specifically, the real-time processing of it.
In general, real-time processing is best suited for analyzing smaller chunks of data that are changing or being added to the system rapidly.
This can prove useful for autonomous cars, for example,where real-time processing of situational sensor data is crucial.
While batch processing is a good fit for certain types of data and computation,other workloads require more real-time processing.
Modern applications are driving the need for low latencies, real-time processing, and the ability to process millions of requests per second.
Real-time processing demands that information be processed and made ready immediately and requires the system to react as new information becomes available.
Event streams offer an alternative:there can be a central platform supporting real-time processing, querying, and computation.
As a consequence, more requirements for real-time processing and more edge computational computing, analysis, and data storage will be dispersed across the network.
This puts pressure on both the computing needs of the platform,since it will require real-time processing of ever-increasing amounts of data.
Applications of this kind do not need real-time processing, meaning this area of digital advertising would work well with blockchain as it stands today.
Data crunching is no longer just for nerds,and the need for sophisticated analysis and powerful, real-time processing is greater than ever.
Real-time processing and reliable data transmission is critical to support telematics, infotainment, driver assistance systems and various sensor data to enable a fully connected vehicle.
While cloud storage capacity has increased significantly over recent years,the need for real-time processing has also seen the rise of edge computing.
It could be to an HP Vertica data warehouse, a MySQL database, an Apache Hadoop system,or an Apache Storm real-time processing system.
The processor alsoincludes two ARM Cortex-M4 processors for offloading real-time processing from the Cortex-A15 cores to improve low-level control and responsiveness of mobile devices.
Spark Streaming was an early addition to Apache Spark that helped it gain traction in environments that required real-time ornear real-time processing.